Technology has developed very quickly regarding handling text obtained through Internet searches, document searches, etc. Text can be easily searched at the touch of a keystroke or the push of a button to find any desired text string. Text that is sorted in order of priority based on one search field can then be re-sorted according to a second search, and so on. The possibilities are virtually limitless.
Technology regarding sorting and ranking images has not progressed nearly as rapidly. This is partly understandable due to the basic differences between alpha-numeric based text strings and images and the greater ease with text-based computers of devising appropriate search strategies for text strings. Nevertheless, it may pose a significant obstacle to certain tasks. Primitive technologies have been developed to make it possible to use a search engine to locate images described by certain text strings. However, it is quite common that such a search may result in undesirable images. Undesirable images may be undesirable for a variety of reasons. They may have too many other distracting elements when it is desired to focus on one canonical item. Contrast between foreground and background may be too low, distracting the viewer. Such images may not be specific enough. They may be insufficiently informative.
Though there is substantial literature on computer vision, most work has focused either on detecting low-level features (edges, texture boundaries, etc.) or high-level semantics (faces, foreground/background, etc.).
It is desirable to develop a system and method for detecting useful images and for ranking images in order of usefulness.